stat.ML

Papers

• Almost Linear Time Consistent Mode Estimation and Quick Shift Clustering (2025)
  Sajjad Hashemian
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• An ensemble diversity approach to supervised binary hashing (2016)
  Miguel \'A. Carreira-Perpi\~n\'an and Ramin Raziperchikolaei
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• Efficient approaches for escaping higher order saddle points in non-convex optimization (2016)
  Anima Anandkumar et al.
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• 2-Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search (2016)
  Ping Li et al.
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• Scalable and Sustainable Deep Learning via Randomized Hashing (2016)
  Ryan Spring et al.
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• Geometry Aware Mappings for High Dimensional Sparse Factors (2016)
  Avradeep Bhowmik et al.
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• Computing Web-scale Topic Models using an Asynchronous Parameter Server (2017)
  Rolf Jagerman et al.
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• Learning a metric for class-conditional KNN (2016)
  Daniel Jiwoong Im et al.
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• Content-based image retrieval tutorial (2016)
  Joani Mitro
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• Random Forest for Label Ranking (2018)
  Yangming Zhou and Guoping Qiu
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• Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation (2016)
  Weihao Gao and Sewoong Oh and Pramod Viswanath
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• ADAGIO: Fast Data-aware Near-Isometric Linear Embeddings (2016)
  Jaros{\l}aw B{\l}asiok et al.
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• The Famine of Forte: Few Search Problems Greatly Favor Your Algorithm (2017)
  George D. Montanez
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• Generalized Intersection Kernel (2016)
  Ping Li
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• Stochastic Generative Hashing (2017)
  Bo Dai et al.
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• k*-Nearest Neighbors: From Global to Local (2017)
  Oren Anava et al.
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• Exemplar-Centered Supervised Shallow Parametric Data Embedding (2017)
  Martin Renqiang Min et al.
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• Fast k-Nearest Neighbour Search via Prioritized DCI (2017)
  Ke Li and Jitendra Malik
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• Leveraging Sparsity for Efficient Submodular Data Summarization (2017)
  Erik M. Lindgren et al.
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• Asymmetric Learning Vector Quantization for Efficient Nearest Neighbor Classification in Dynamic Time Warping Spaces (2017)
  Brijnesh Jain and David Schultz
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• Comparison Based Nearest Neighbor Search (2017)
  Siavash Haghiri et al.
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• Scaling Active Search using Linear Similarity Functions (2017)
  Sibi Venkatesan et al.
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• Open Loop Hyperparameter Optimization and Determinantal Point Processes (2019)
  Jesse Dodge et al.
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• A simple efficient density estimator that enables fast systematic search (2017)
  Jonathan R. Wells and Kai Ming Ting
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• Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search (2017)
  Stephen Mussmann et al.
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• Asymmetric Deep Supervised Hashing (2017)
  Qing-Yuan Jiang et al.
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• Privacy Preserving Identification Using Sparse Approximation with Ambiguization (2017)
  Behrooz Razeghi et al.
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• A Parallel Best-Response Algorithm with Exact Line Search for Nonconvex Sparsity-Regularized Rank Minimization (2017)
  Yang Yang et al.
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• Simple And Efficient Architecture Search for Convolutional Neural Networks (2017)
  Thomas Elsken et al.
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• Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science (2017)
  George C. Linderman et al.
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• A Resizable Mini-batch Gradient Descent based on a Multi-Armed Bandit (2018)
  Seong Jin Cho et al.
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• Practical Hash Functions for Similarity Estimation and Dimensionality Reduction (2017)
  S{\o}ren Dahlgaard et al.
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• Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding (2019)
  George C. Linderman et al.
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• Toward Metric Indexes for Incremental Insertion and Querying (2018)
  Edward Raff and Charles Nicholas
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• Learning Correlation Space for Time Series (2018)
  Han Qiu et al.
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• Revisiting the Vector Space Model: Sparse Weighted Nearest-Neighbor Method for Extreme Multi-Label Classification (2018)
  Tatsuhiro Aoshima et al.
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• A Progressive Batching L-BFGS Method for Machine Learning (2018)
  Raghu Bollapragada et al.
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• Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours (2018)
  Henry WJ Reeve et al.
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• Gradient Augmented Information Retrieval with Autoencoders and Semantic Hashing (2018)
  Sean Billings
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• Ranking with Adaptive Neighbors (2018)
  Muge Li et al.
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• Bernoulli Embeddings for Graphs (2018)
  Vinith Misra and Sumit Bhatia
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• Fast Counting in Machine Learning Applications (2019)
  Subhadeep Karan et al.
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• Exact Distributed Training: Random Forest with Billions of Examples (2018)
  Mathieu Guillame-Bert and Olivier Teytaud
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• An $O(N)$ Sorting Algorithm: Machine Learning Sort (2018)
  Hanqing Zhao et al.
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• Efficient end-to-end learning for quantizable representations (2018)
  Yeonwoo Jeong et al.
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• Bandit-Based Monte Carlo Optimization for Nearest Neighbors (2021)
  Vivek Bagaria et al.
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• Monte Carlo Tree Search for Asymmetric Trees (2018)
  Thomas M. Moerland et al.
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• Pattern Search Multidimensional Scaling (2019)
  Georgios Paraskevopoulos and Efthymios Tzinis and Emmanouil-Vasileios Vlatakis-Gkaragkounis and Alexandros Potamianos
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• Searching for a Single Community in a Graph (2018)
  Avik Ray et al.
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• Approximate Nearest Neighbor Search in High Dimensions (2018)
  Alexandr Andoni et al.
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